Physical and chemical characteristics of Maytenus rigida in different particle sizes using SEM/EDS, TG/DTA and pyrolysis GC-MS

作者:Correia Lidiane Pinto; de Santana Cleildo Pereira; Alves da Silva Karla Monik; de Lima Ramos Junior Fernando Jose; Cunha Lima Rosemary Sousa; de Souza Fabio Santos; Dantas de Medeiros Ana Claudia; Macedo Rui Oliveira
来源:Journal of Thermal Analysis and Calorimetry, 2018, 131(1): 743-752.
DOI:10.1007/s10973-016-5999-0

摘要

Thermoanalytical techniques have been widely applied in the characterization of herbal medicines, providing data about the herbal products quality. The objective of this work was to use analytical techniques for the Maytenus rigida powder in different particle sizes characterization. The techniques used were scanning electron microscopy (SEM) with energy-dispersive spectroscopy, differential thermal analysis (DTA), Thermogravimetry (TG), using the model of Ozawa to evaluate the kinetic parameters and gas chromatography coupled to pyrolysis/mass spectrometry (PYR-GC/MS). Different particle morphologies and size were verified by SEM. The thermoanalytical techniques (TG and DTA) showed physical and chemical processes occurred. Different degradation profiles curves were obtained when the samples were exposed to the atmosphere of nitrogen and synthetic air. Kinetic data showed different activation energy values and the same reaction order to the studied samples. Through Ozawa kinetic parameters, it was possible to observe granulometries distinctions to the herbal medicine powder batches. Pyrolysis allowed to correlate TG decomposition data with the identification of its degradation products and showed two similar compounds among the samples at lower temperatures (250 A degrees C) and at higher temperatures (600 A degrees C). The fingerprint of the degradation components by PYR-GC-MS and the other analytical tools has been utilized as an alternative to the quality control of herbal medicine evaluation. E (a) obtained by dynamic TG in air synthetic atmosphere was the parameter which better differentiate the samples.

  • 出版日期2018-1